Abstract Learning from Demonstration (LfD) seeks to democratize robotics by enabling non-
roboticist end-users to teach robots to perform a task by providing a human demonstration …

We address the problem of enabling quadrupedal robots to perform precise shooting skills
in the real world using reinforcement learning. Develo** algorithms to enable a legged …

In this paper, we address the discovery of robotic options from demonstrations in an
unsupervised manner. Specifically, we present a framework to jointly learn low-level control …

In the future, robots will be used more extensively as assistants in home scenarios and must
be able to acquire expertise from trainers by learning through crossmodal interaction. One …

In this paper, we present an approach to learn recomposable motor primitives across large-
scale and diverse manipulation demonstrations. Current approaches to decomposing …

Just like humans, robots can improve their performance by practicing, ie by performing the
desired behavior many times and updating the underlying skill representation using the …

Learning long-range behaviors on complex high-dimensional agents is a fundamental
problem in robot learning. For such tasks, we argue that transferring learned information …

Reinforcement learning (RL) has achieved tremendous success as a general framework for
learning how to make decisions. However, this success relies on the interactive hand-tuning …

Recently robots are being used more frequently as assistants in domestic scenarios. In this
context we train an apprentice robot to perform a cleaning task using interactive …

Reinforcement learning (RL) has achieved some impressive recent successes in various
computer games and simulations. Most of these successes are based on having large …